ArticleGenes & genomics2026
Single-cell transcriptomics and machine learning identify RNF144B and C5AR1 as immune-related molecular signatures and therapeutic targets in myocardial infarction.
Article in Genes & genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundMyocardial infarction (MI) is a life-threatening cardiovascular disease characterized by high morbidity and mortality. Although advances in clinical management have improved patient outcomes, early diagnosis and effective immunomodulatory therapies remain limited.
objectiveThis paper aims to identify key regulatory genes in MI, uncover their underlying mechanisms of action of the key genes, and facilitate their diagnostic and therapeutic use.
methodsIn this study, we integrated multiple transcriptomic datasets and applied machine learning approaches, including LASSO regression, to identify a robust 13 key genes significantly associated with MI. GSEA and GSVA were subsequently performed to explore their potential biological functions. The immunological relevance of these genes was evaluated by analyzing their correlations with inflammation-related genes and those involved in immune cell migration. In addition, transcription factor and microRNA (miRNA) regulatory networks were constructed to elucidate upstream regulatory mechanisms. The expression levels of the 13 key genes were validated in MI mouse model.
resultsAmong 11 cardiac cell populations identified, myeloid cells contributed most prominently to MI pathogenesis. A robust 13-gene predictive signature was established, with RNF144B and C5AR1 showing strong associations with immune modulation and disease severity. Correlation analysis demonstrated a significant positive relationship of RNF144B and C5AR1 with immunological roles. TF-gene and miRNA–mRNA regulatory networks supported the post-transcriptional regulation of these genes. In the MI mouse model, expression of the 13 genes was consistent with the risk-prediction model. Molecular docking identified CCX168 as a promising small-molecule candidate targeting RNF144B and C5AR1.
conclusionThis study identified 13-gene signature, particularly RNF144B and C5AR1, holds promise as therapeutic targets, providing new insights for immunomodulatory and precision medicine strategies in MI.
Indexed as
Identifiers
41984330What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.